Problem
Research questions and friction points this paper is trying to address.
Integrated Sensing and Communication
LEO Satellite Systems
Cross-functional Interference
Channel Phase Uncertainty
Resource Constraints
Robust Design of Integrated Sensing and Communication in LEO Satellite Systems
🤖 AI Summary
This work addresses the challenge of limited spectrum and orbital resources in low Earth orbit (LEO) satellite systems, which hinder the simultaneous efficient support of communication and sensing functionalities. To overcome this, the paper proposes an integrated sensing and communication (ISAC) framework tailored for LEO satellites, enabling a single satellite to concurrently serve multiple communication users and sense multiple targets over the same frequency band. To mitigate cross-functional interference caused by channel phase uncertainty, a novel robust beamforming algorithm is developed that minimizes transmit power while guaranteeing both communication signal-to-interference-plus-noise ratio (SINR) and sensing mean squared error (MSE) performance. Theoretical analysis and simulations demonstrate that the proposed approach significantly outperforms existing baseline schemes in terms of power efficiency and system robustness.
📝 Abstract
With the growing demand for satellite sensing and communication, the limited wireless resources are difficult to support multiple satellite systems. Therefore, it is desired to investigate integrated sensing and communication (ISAC) in low Earth orbit (LEO) satellite systems to enable multi-functionality within a single satellite, thereby saving both spectrum and orbital resources. In this paper, a framework for ISAC in LEO satellite systems is established, where a satellite can simultaneously sense multiple targets and serve multiple communication users (CUs) over the same spectrum. Considering the limited onboard energy of satellite, a novel robust beamforming design algorithm is developed with the goal of minimizing total transmit power while satisfying the mean squared error (MSE) requirements for sensing and signal-to-interference-plus-noise ratio (SINR) requirements for communication in presence of channel phase uncertainty which exacerbates the cross-functional interference. According to theoretical analysis, the proposed algorithm for ISAC in LEO satellite systems is effective. Moreover, extensive simulations confirm the superiority of the proposed algorithm over baselines.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Integrated Sensing and Communication (ISAC)
LEO satellite systems
robust beamforming
channel phase uncertainty
cross-functional interference
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